Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

Laurie, S., Piscia, D., Matalonga, L., Corvó, A., Fernández-Callejo, M., Garcia-Linares, C., et al. (2022). The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases. HUMAN MUTATION, 43(6), 717-733 [10.1002/humu.24353].

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases

Licata, Luana;
2022-06-01

Abstract

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.
giu-2022
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore BIO/18 - GENETICA
English
Con Impact Factor ISI
NGS; data sharing; data standardization; diagnostics; genome analysis; patient matchmaking; rare diseases
Laurie, S., Piscia, D., Matalonga, L., Corvó, A., Fernández-Callejo, M., Garcia-Linares, C., et al. (2022). The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases. HUMAN MUTATION, 43(6), 717-733 [10.1002/humu.24353].
Laurie, S; Piscia, D; Matalonga, L; Corvó, A; Fernández-Callejo, M; Garcia-Linares, C; Hernandez-Ferrer, C; Luengo, C; Martínez, I; Papakonstantinou, A; Picó-Amador, D; Protasio, J; Thompson, R; Tonda, R; Bayés, M; Bullich, G; Camps-Puchadas, J; Paramonov, I; Trotta, J; Alonso, A; Attimonelli, M; Béroud, C; Bros-Facer, V; Buske, Oj; Cañada-Pallarés, A; Fernández, Jm; Hansson, Mg; Horvath, R; Jacobsen, Job; Kaliyaperumal, R; Lair-Préterre, S; Licata, L; Lopes, P; López-Martín, E; Mascalzoni, D; Monaco, L; Pérez-Jurado, La; Posada de la Paz, M; Rambla, J; Rath, A; Riess, O; Robinson, Pn; Salgado, D; Smedley, D; Spalding, D; 't Hoen, Pac; Töpf, A; Zaharieva, I; Graessner, H; Gut, Ig; Lochmüller, H; Beltran, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/325244
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